Purpose This paper aims to prepare a full operational readiness by establishing an optimal flight plan considering the weather conditions in order to effectively perform the mission and operation of military aircraft. This paper suggests a flight prediction model and rules by analyzing the correlation between flight implementation and cancellation according to weather conditions by using big data collected from historical flight information of military aircraft supplied by Korean manufacturers and meteorological information from the Korea Meteorological Administration. In addition, by deriving flight rules according to weather information, it was possible to discover an efficient flight schedule establishment method in consideration of weather information. Design/methodology/approach This study is an analytic study using data mining techniques based on flight historical data of 44,558 flights of military aircraft accumulated by the Republic of Korea Air Force for a total of 36 months from January 2013 to December 2015 and meteorological information provided by the Korea Meteorological Administration. Four steps were taken to develop optimal flight prediction models and to derive rules for flight implementation and cancellation. First, a total of 10 independent variables and one dependent variable were used to develop the optimal model for flight implementation according to weather condition. Second, optimal flight prediction models were derived using algorithms such as logistics regression, Adaboost, KNN, Random forest and LightGBM, which are data mining techniques. Third, we collected the opinions of military aircraft pilots who have more than 25 years experience and evaluated importance level about independent variables using Python heatmap to develop flight implementation and cancellation rules according to weather conditions. Finally, the decision tree model was constructed, and the flight rules were derived to see how the weather conditions at each airport affect the implementation and cancellation of the flight. Findings Based on historical flight information of military aircraft and weather information of flight zone. We developed flight prediction model using data mining techniques. As a result of optimal flight prediction model development for each airbase, it was confirmed that the LightGBM algorithm had the best prediction rate in terms of recall rate. Each flight rules were checked according to the weather condition, and it was confirmed that precipitation, humidity, and the total cloud had a significant effect on flight cancellation. Whereas, the effect of visibility was found to be relatively insignificant. When a flight schedule was established, the rules will provide some insight to decide flight training more systematically and effectively.
International Journal of Computer Science & Network Security
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v.22
no.5
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pp.79-88
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2022
Modern production requires production staff who have design competence, experience and skills to work in various types of work integrated into professional activities. Possession of digital design methods significantly expands the opportunities for professional activities of qualified workers. The purpose of our study was to study the impact of pedagogical conditions on the formation of design competence of future qualified workers in a group work. We have identified a set of pedagogical conditions that promote the development of professionally oriented artistic and technical creativity of workers in the conditions of curricular and extracurricular activities, which include motivational-target, procedural-semantic, organizational-technological, and subject-oriented. It is shown that the formation of design competence is determined by motivational, informational-active and reflection criteria, which are aimed at motivational-value, cognitive, operational-active, creative, social and emotional components of this competence. The methodology of the research is highlighted, which includes the use of the following methods: determination of the personality's motivational sphere in order to identify strong and weak motives of students activity; multiple intelligence to identify students talents in the direction of practical intelligence, which is important for design competence; determining the level of creative activity to identify manifestations of students creative abilities; identifying the type of students innovative thinking in order to develop motivation for success; factor-criterion model, developed on the basis of a qualimetric approach, which is used to identify the level of design competence formation in accordance with its components. The results of the study showed that the creation of separate pedagogical conditions in the institution of vocational education and training (VET) had a positive impact on the development of design competence, which shows the potential of artistic and technical design in the development of professional creativity of future qualified workers taking into account the environmental approach.
This study aimed to investigate elementary school teachers' interest in mathematics textbooks following the new change in the publication system for elementary mathematics textbooks. To achieve this, an online survey platform was used to conduct a survey of elementary school teachers in teaching grade 3-4 across the country, and the responses of 199 participants were analyzed to determine their interest in mathematics textbooks. The research results showed that elementary school teachers had high levels of interest in mathematics textbooks, particularly in informational and personal interest. Moreover, the stages at which teachers showed the highest level of interest were reinforcement interest and operational interest. Analysis of the differences in interest in mathematics textbooks based on personal variables showed significant differences depending on the teacher's experience in mathematics education training, satisfaction with mathematics textbooks, and whether they majored in mathematics education. Based on these findings, it can be inferred that elementary school teachers have a high level of informational interest in the characteristics, strengths, weaknesses, and materials related to authorized and approved mathematics textbooks, and their high level of personal interest in mathematics textbooks can have a positive effect in line with the goal of the new textbook system. Additionally, since many teachers showed a high level of interest in reinforcement interest, it is necessary to devise various ways to support teachers' creative use and reconstruction of mathematics textbooks.
Smart museums based on the growth of online exhibition can be seen as in line with the movement of the 4th Industrial Revolution. By combining art and technologies, they enable viewers to experience culture and art. This study examined the cases of the Dunhuang Museum, the Palace Museum, and the China Arts and Crafts Master Museum to assess or identify how China is leading by accepting the technology of the fourth industry and applying the technology. In common, Chinese smart museums are widely used for collecting enviromental data, establishing integrated digital applications, and preserving collections, services, management, and exhibitions through VR, and AR. Through the case of the Chinese Smart Museum, this study identified the online exhibition as a space that exists in another dimension rather than an image replica with excellent operational utility. Therefore, online exhibitions are the best medium to expand the space, and viewers can explorethe museum's exhibition room and engage with all the contents of the museum without visiting the museum in person. Through the online exhibition of smart museums, visitors and viewers can be transformed into more active cultural consumers and develop collective capabilities.
Proceedings of the Korean Institute of Navigation and Port Research Conference
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2023.05a
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pp.57-58
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2023
The working time for loading and transporting containers in the container terminal is one of the factors directly related to port productivity, and minimizing working time for these operations can maximize port productivity. Among working time for container operations, the working time of yard tractors(Y/T) responsible for the transportation of containers between berth and yard is a significant portion. However, it is difficult to estimate the working time of yard tractors quantitatively, although it is possible to estimate it based on the practical experience of terminal operators. Recently, a technology based on IoT(Internet of Things), one of the core technologies of the 4th industrial revolution, is being studied to monitoring and tracking logistics resources within the port in real-time and calculate working time, but it is challenging to commercialize this technology at the actual port site. Therefore, this study aims to develop yard tractor working time prediction model to enhance the operational efficiency of the container terminal. To develop the prediction model, we analyze actual port operation data to identify factors that affect the yard tractor's works and predict its working time accordingly.
Journal of the Korean Society of Marine Environment & Safety
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v.29
no.7
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pp.964-970
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2023
As part of the International Maritime Organization ef orts to reduce greenhouse gas emissions, the maritime industry is exploring low-carbon fuels such as liquefied natural gas and methanol, as well as zero-carbon fuels such as hydrogen and ammonia, evaluating them as environmentally friendly alternatives. Particularly, ammonia has substantial operational experience as cargo on transport ships, and ammonia ship engines are expected to be available in the second half of 2024, making it relatively accessible for commercial use. However, overcoming the toxicity challenges associated with using ammonia as a fuel is imperative. Detection is possible at levels as low as 5 ppm through olfactory senses, and exposure to concentrations exceeding 300 ppm for more than 30 min can result in irreparable harm. Using the KORA program provided by the Chemical Safety Agency, an assessment of the potential risks arising from leaks during ammonia bunkering was conducted. A 1-min leak could lead to a 5 ppm impact within a radius of approximately 7.5 km, affecting key areas in Busan, a major city. Furthermore, the potentially lethal concentration of 300 ppm could have severe consequences in densely populated areas and schools near the bunkering site. Therefore, given the absence of regulations related to ammonia bunkering, the potential for widespread toxicity from even minor leaks highlights the requirement for the development of legislation. Establishing an integrated system involving local governments, fire departments, and environmental agencies is crucial for addressing the potential impacts and ensuring the safety of ammonia bunkering operations.
Journal of the Korean BIBLIA Society for library and Information Science
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v.34
no.4
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pp.183-205
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2023
This study was conducted to identify the operation status of Dobong-gu public libraries in order to establish a mid- to long-term development plan for Dobong-gu libraries, and to analyze local residents' perceptions of libraries by factors through user surveys to suggest specific development plans for Dobong-gu libraries. Overall, the satisfaction level of Dobong-gu residents with library services was found to be high, and all libraries were analyzed to be providing high-quality services. From this, the following operational strategies for the mid- to long-term development plan of Dobong-gu public libraries can be derived. First, libraries need to continue to collect and provide books that meet the quantitative and qualitative levels to satisfy the needs of the community and users. Electronic and online materials, including e-books and audiobooks, as well as subject-specific materials should be expanded to provide relevant programs. Second, although Dobong-gu is an aging city, a wide range of age live there, so there is a need to promote communication and understanding between generations and promote integration of the community through a generational empathy program. Third, it is necessary to remodel and improve the space of aging libraries by organizing library facilities and environments into open spaces and creating makerspaces and multicultural spaces for direct experience and practice, reflecting the latest trends in library space organization.
Joo Wan Cha;Bu-Yo Kim;Miloslav Belorid;Yonghun Ro;A-Reum Ko;Sun Hee Kim;Dong-Ho Park;Ji Man Park;Hae Jung Koo;Ki-Ho Chang;Hong Hee Lee;Soojong Kim
Atmosphere
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v.34
no.2
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pp.203-216
/
2024
The National Institute of Meteorological Sciences in Korea has developed the Weather Modification Hybrid Rocket (WMHR), an advanced system that offers enhanced stability and cost-effectiveness over conventional solid-fuel rockets. Designed for precise operation, the WMHR enables accurate control over the ejection altitude of pyrotechnics by modulating the quantity of oxidizer, facilitating specific cloud seeding at various atmospheric layers. Furthermore, the rate of descent for pyrotechnic devices can be adjusted by modifying parachute sizes, allowing for controlled dispersion time and concentration of seeding agents. The rocket's configuration also supports adjustments in the pyrotechnic device's capacity, permitting tailored seeding agent deployment. This innovation reflects significant technical progression and collaborations with local manufacturers, in addition to efforts to secure testing sites and address hybrid rocket production challenges. Notable outcomes of this project include the creation of a national framework for weather modification technology utilizing hybrid rockets, enhanced cloud seeding methods, and the potential for broader meteorological application of hybrid rockets beyond precipitation augmentation. An illustrative case study confirmed the WMHR's operational effectiveness, although the impact on cloud seeding was limited by unfavorable weather conditions. This experience has provided valuable insights and affirmed the system's potential for varied uses, such as weather modification and deploying high-altitude meteorological sensors. Nevertheless, the expansion of civilian weather rocket experiments in Korea faces challenges due to inadequate infrastructure and regulatory limitations, underscoring the urgent need for advancements in these areas.
The objective of the study is to explore the relationships between the variables of nursing productivity on the framework of system del in the tertiary university based care hospital in Korea. Productivity is basically defined as the relation-ship between inputs and outputs. Under the proposition that the nursing unit is a system that produces nursing care output using personal and material resources through the nursing intervention and nursing care management. And this major conception of nursing productivity system comproises input, process and output and feed-back. These categorized variables are essential parts to produce desirable and meaningful out-put. While nursing personnel from head nurse to staff nurses cooperate with each other, the head nurse directs her subordinates to achieve the goal of nursing care unit. In this procedure, the head nurse uses the leadership of authority and benevolence. Meantime nursing productivity will be greatly influenced by environment and surrounding organizational structures, and by also the operational objectives, the policy and standards of procedures. For the study of nursing productivity one sample hospital with 15 general nursing care units was selected. Research data were collected for 3 weeks from May 31 to June 20 in 1993. Input variables were measured in terms of both the served and the server. And patient classification scores were measured drily by degree of nursing care needs that indicated patent case-mix. And also nurses' educational period for profession and clinical experience and the score of nurses' personality were measured as producer input variables by the questionnaires. The process varialbes act necessarily on leading input resources and result in desirable nursing outputs. Thus the head nurse's leadership perceived by her followers is defined as process variable. The output variables were defined as length of stay, average nursing care hours per patient a day the score of quality of nursing care, the score of patient satisfaction, the score of nurse's job satis-faction. The nursing unit was the basis of analysis, and various statistical analyses were used : Reliability analysis(Cronbach's alpha) for 5 measurement tools and Pearson-correlation analysis, multiple regression analysis, and canonical correlation analysis for the test of the relationship among the variables. The results were as follows : 1. Significant positive relationship between the score of patient classification and length of stay was found(r=.6095, p.008). 2. Regression coefficient between the score of patient classification and length of stay was significant (β=.6245, p=.0128), and variance explained was 39%. 3. Significant positive relationship between nurses’ educational period and length of stay was found(r=-.4546, p=.044). 5. Regression coefficient between nurses' educational period and the score of quality of nursing care was significant (β=.5600, p=.029), and variance explained was 31.4%. 6. Significant positive relationship between the score of head nurse's leadership of authoritic characteristics and the length of stay was found (r=.5869, p=.011). 7. Significant negative relationship between the score of head nurse's leadership of benevolent characteristics and average nursing care hours was found(r=-.4578, p=.043). 8. Regression coefficient between the score of head nurse's leadership of benevolent characteristics and average nursing care hours was significant(β=-.6912, p=.0043), variance explained was 47.8%. 9. Significant positive relationship between the score of the head nurse's leadership of benevolent characteristics and the score of nurses' job satis-faction was found(r=.4499, p=050). 10. A significant canonical correlation was found between the group of the independent variables consisted of the score of the nurses' personality, the score of the head nurse's leadership of authoritic characteristics and the group of the dependent variables consisted of the length of stay, average nursing care hours(Rc²=.4771, p=.041). Through these results, the assumed relationships between input variables, process variable, output variables were partly supported. In addition it is also considered necessary that-further study on the relationships between nurses' personality and nurses' educational period, between nurses' clinical experience including skill level and output variables in many research samples should be made.
Due to the wide spread of customers' frequent access of non face-to-face services, there have been many attempts to improve customer satisfaction using huge amounts of data accumulated throughnon face-to-face channels. Usually, a call center is regarded to be one of the most representative non-faced channels. Therefore, it is important that a call center has enough agents to offer high level customer satisfaction. However, managing too many agents would increase the operational costs of a call center by increasing labor costs. Therefore, predicting and calculating the appropriate size of human resources of a call center is one of the most critical success factors of call center management. For this reason, most call centers are currently establishing a department of WFM(Work Force Management) to estimate the appropriate number of agents and to direct much effort to predict the volume of inbound calls. In real world applications, inbound call prediction is usually performed based on the intuition and experience of a domain expert. In other words, a domain expert usually predicts the volume of calls by calculating the average call of some periods and adjusting the average according tohis/her subjective estimation. However, this kind of approach has radical limitations in that the result of prediction might be strongly affected by the expert's personal experience and competence. It is often the case that a domain expert may predict inbound calls quite differently from anotherif the two experts have mutually different opinions on selecting influential variables and priorities among the variables. Moreover, it is almost impossible to logically clarify the process of expert's subjective prediction. Currently, to overcome the limitations of subjective call prediction, most call centers are adopting a WFMS(Workforce Management System) package in which expert's best practices are systemized. With WFMS, a user can predict the volume of calls by calculating the average call of each day of the week, excluding some eventful days. However, WFMS costs too much capital during the early stage of system establishment. Moreover, it is hard to reflect new information ontothe system when some factors affecting the amount of calls have been changed. In this paper, we attempt to devise a new model for predicting inbound calls that is not only based on theoretical background but also easily applicable to real world applications. Our model was mainly developed by the interactive decision tree technique, one of the most popular techniques in data mining. Therefore, we expect that our model can predict inbound calls automatically based on historical data, and it can utilize expert's domain knowledge during the process of tree construction. To analyze the accuracy of our model, we performed intensive experiments on a real case of one of the largest car insurance companies in Korea. In the case study, the prediction accuracy of the devised two models and traditional WFMS are analyzed with respect to the various error rates allowable. The experiments reveal that our data mining-based two models outperform WFMS in terms of predicting the amount of accident calls and fault calls in most experimental situations examined.
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